Painful Disorders of Gut‐Brain Interaction Are More Associated With Worse Health‐Related Quality of Life and Psychological Disorders Than Non‐Painful Disorders in Latin American Countries
Bibliographic record
Abstract
BACKGROUND: Disorders of gut-brain interaction (DGBI) are associated with reduced health-related quality of life (HRQoL) and psychological disorders. Among individuals with DGBI, abdominal pain correlates with increased healthcare-seeking and analgesic use. This study aimed to evaluate the influence of pain as a cardinal symptom on HRQoL and psychological disorders. METHODS: This is a sub-analysis of data from four Latin American countries included in the Rome Foundation Global Epidemiology Study (RFGES). DGBI were classified into (1) painful DGBI, including individuals with diagnoses characterized by pain as a primary symptom, and (2) non-painful DGBI, including individuals with only non-painful diagnoses. Prevalence rates, healthcare-seeking behavior, HRQoL (Patient-Reported Outcomes Measurement Information System Global-10 [PROMIS Global-10]), anxiety and depression (Patient Health Questionnaire-4 [PHQ-4]) and somatization (Patient Health Questionnaire-12 [PHQ-12]) were compared. KEY RESULTS: A total of 8069 participants from the four countries completed the RFGES online survey, including 1132 in the painful group and 1720 in the non-painful group. Participants with painful DGBI more commonly sought healthcare at least monthly compared to those with non-painful disorders (18.6% vs. 14.9%). Painful disorders were associated with significantly lower HRQoL scores and higher PHQ-4 and PHQ-12 scores, both in unadjusted and adjusted analyses (sex, age, education, and community size). CONCLUSION AND INFERENCES: In four Latin American countries, individuals with painful DGBI were more likely to seek healthcare, had worse HRQoL and exhibited greater psychological distress compared to those with non-painful DGBI. These findings highlight the need for targeted interventions for individuals with painful DGBI symptoms.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".